class_docstr: Retrieves most similar terms for a given term under the hypothesis that the similarities between
  distinct terms are uniform.
  
  Parameters
  ----------
  dictionary : :class:`~gensim.corpora.dictionary.Dictionary`
      A dictionary that specifies the considered terms.
  term_similarity : float, optional
      The uniform similarity between distinct terms.
  
  See Also
  --------
  :class:`~gensim.similarities.termsim.SparseTermSimilarityMatrix`
      A sparse term similarity matrix built using a term similarity index.
  
  Notes
  -----
  This class is mainly intended for testing SparseTermSimilarityMatrix and other classes that
  depend on the TermSimilarityIndex.
code: def most_similar(self, t1, topn=10):
      for __, (t2_index, t2) in zip(
          range(topn),
          (
              (t2_index, t2)
              for t2_index, t2 in self.dictionary
              if t2 != t1
          ),
      ):
          yield (t2, self.term_similarity)
  
imports: from array import array
  from itertools import chain
  import logging
  from math import sqrt
  import numpy
  from scipy import sparse
  from gensim.matutils import corpus2csc
  from gensim.utils import SaveLoad, is_corpus
label_desc: Use image node_id 2 for calling the UniformTermSimilarityIndex obj's underlying member method code with example usage: obj.most_similar(t1, topn) without return types